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Kernel Method - What is the working rule for kernel method?


An important property of kernel approaches is their capacity to transform nonlinear regression problems from input space X to feature space F, where the issue can then be expressed as a linear one. In order to implement kernel algorithms, the input space X is transformed into a high-dimensional reproducing Basic Hilbert Space Area H via a transformation ϕ: X → H.